The PhD project is focused on designing computational methods for gRNA design while taking the off-target landscape, developed by others in the group, into account. The PhD project will take outset in the in-house deep learning (DL) model, CRISPRon, to be applied on data generated by project collaborator Prof Yonglun Luo. The initial model will encode both on- and off-target data (as ranked by our CRISPRoff method) to predict gRNA efficiency while also being used for model-driven data generation of novel gRNA efficiency data by collaborator. The downstream computational models will explore machine and deep learning techniques for further enhancement.
Professional qualifications relevant to the PhD project. This include (but not limited to):
For the following criteria the level has to be at level where you are able to work independently:
A solid knowledge of Machine and Deep learning algorithms
Python (or Perl) and knowledge of C/C++, shell scripting and Unix/Linux operating system
Previous publications
Relevant work experience
the full description and application procedure is available here:
jobportal.ku.dk/phd/?show=159733